Wavelet Integrated CNNs for Noise-Robust Image Classification

CVPR 2020 Qiufu LiLinlin ShenSheng GuoZhihui Lai

Convolutional Neural Networks (CNNs) are generally prone to noise interruptions, i.e., small image noise can cause drastic changes in the output. To suppress the noise effect to the final predication, we enhance CNNs by replacing max-pooling, strided-convolution, and average-pooling with Discrete Wavelet Transform (DWT)... (read more)

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